This article aims to study the processing methods by exploring the main chemical constituents of Aconiti Lateralis Radix Praeparata and the toxicity-attenuating mechanisms. The relevant articles were retrieved from multiple databases with the time interval of 1960-2024, and the chemical constituents of Aconiti Lateralis Radix Praeparata and the toxicity-attenuating mechanisms of its processing methods were summarized. The review revealed that the chemical constituents of Aconiti Lateralis Radix Praeparata included 32 diester-type alkaloids, 36 monoester-type alkaloids, 43 alkanolamine-type alkaloids, and 8 lipid-type alkaloids. At the same time, other chemical constituents such as water-soluble alkaloids were also studied, and their pharmacological activities were summarized. The toxicity-attenuating mechanisms of the processing methods included constituent loss, hydrolysis, ester exchange, and ion-pair action. The processing methods of Aconiti Lateralis Radix Praeparata have developed from being traditional to modern, with simplified operation and increased retention amounts of active constituents, which have improved the efficacy of processed Aconiti Lateralis Radix Praeparata products and have facilitated the industrial production. However, the existing processing methods of Aconiti Lateralis Radix Praeparata cannot completely solve the problem of possible reduction in efficacy during toxicity attenuation. More toxicity-attenuating mechanisms and lipid-type alkaloids of Aconiti Lateralis Radix Praeparata should be explored, which is expected to reduce its toxicity while retaining its efficacy.
Aconitum/toxicity* ; Drugs, Chinese Herbal/isolation & purification* ; Alkaloids/chemistry* ; Animals ; Humans

This study explored the mechanism of Xiangsha Liujunzi Decoction(XSLJZD) in the treatment of functional dyspepsia(FD) based on inositol-requiring enzyme 1(IRE1)/apoptosis signal-regulating kinase 1(ASK1)/c-Jun N-terminal kinase(JNK) pathway-mediated autophagy in interstitial cells of Cajal(ICC). Forty-eight SPF-grade male SD suckling rats were randomly divided into a blank group and a modeling group, and the integrated modeling method(iodoacetamide gavage + disturbance of hunger and satiety + swimming exhaustion) was used to replicate the FD rat model. After the model replications were successfully completed, the rats were divided into a model group, high-dose, medium-dose, and low-dose groups of XSLJZD(12, 6, and 3 g·kg~(-1)·d~(-1)), and a positive drug group(mosapride of 1.35 mg·kg~(-1)·d~(-1)), and the intervention lasted for 14 days. The gastric emptying rate and intestinal propulsion rate of rats in each group were measured. The histopathological changes in the gastric sinus tissue of rats in each group were observed by hematoxylin-eosin(HE) staining. The ultrastructure of ICC was observed by transmission electron microscopy. The immunofluorescence double staining technique was used to detect the protein expression of phospho-IRE1(p-IRE1), TNF receptor associated factors 2(TRAF2), phospho-ASK1(p-ASK1), phospho-JNK(p-JNK), p62, and Beclin1 in ICC of gastric sinus tissue of rats in each group. Western blot was used to detect the related protein expression of gastric sinus tissue of rats in each group. Compared with those in the blank group, the rats in the model group showed decreased body weight, gastric emptying rate, and intestinal propulsion rate, and transmission electron microscopy revealed damage to the endoplasmic reticulum structure and increased autophagosomes in ICC. Immunofluorescence staining revealed that the ICC of gastric sinus tissue showed a significant elevation of p-IRE1, TRAF2, p-ASK1, p-JNK, and Beclin1 proteins and a significant reduction of p62 protein. Western blot revealed that the expression levels of relevant proteins in gastric sinus tissue were consistent with those of proteins in ICC. Compared with the model group, the body weight of rats in the high-dose and medium-dose groups of XSLJZD was increased, and the gastric emptying rate and intestinal propulsion rate were increased. Transmission electron microscopy observed amelioration of structural damage to the endoplasmic reticulum of ICC and reduction of autophagosomes, and the p-IRE1, TRAF2, p-ASK1, p-JNK, and Beclin1 proteins in the ICC of gastric sinus tissue were significantly decreased. The p62 protein was significantly increased. Western blot revealed that the expression levels of relevant proteins in gastric sinus tissue were consistent with those of proteins in ICC. XSLJZD can effectively treat FD, and its specific mechanism may be related to the inhibition of the expression of molecules related to the endoplasmic reticulum stress IRE1/ASK1/JNK pathway in ICC and the improvement of autophagy to promote gastric motility in ICC.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Autophagy/drug effects* ; Rats ; Rats, Sprague-Dawley ; Interstitial Cells of Cajal/metabolism* ; Dyspepsia/physiopathology* ; Protein Serine-Threonine Kinases/genetics* ; MAP Kinase Kinase Kinase 5/genetics* ; MAP Kinase Signaling System/drug effects* ; Humans ; Endoribonucleases/genetics* ; Multienzyme Complexes

This study aims to explore the pharmacodynamic material basis of Jinbei Oral Liquid(JBOL) against idiopathic pulmonary fibrosis(IPF) based on serum pharmacochemistry and network pharmacology. The ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS/MS) technology was employed to analyze and identify the components absorbed into rat blood after oral administration of JBOL. Combined with network pharmacology, the study explored the pharmacodynamic material basis and potential mechanism of JBOL against IPF through protein-protein interaction(PPI) network construction, "component-target-pathway" analysis, Gene Ontology(GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis. First, a total of 114 compounds were rapidly identified in JBOL extract according to the exact relative molecular mass, fragment ions, and other information of the compounds with the use of reference substances and a self-built compound database. Second, on this basis, 70 prototype components in blood were recognized by comparing blank serum with drug-containing serum samples, including 28 flavonoids, 25 organic acids, 4 saponins, 4 alkaloids, and 9 others. Finally, using these components absorbed into blood as candidates, the study obtained 212 potential targets of JBOL against IPF. The anti-IPF mechanism might involve the action of active ingredients such as glycyrrhetinic acid, cryptotanshinone, salvianolic acid B, and forsythoside A on core targets like AKT1, TNF, and ALB and thereby the regulation of multiple signaling pathways including PI3K/AKT, HIF-1, and TNF. In conclusion, JBOL exerts the anti-IPF effect through multiple components, targets, and pathways. The results would provide a reference for further study on pharmacodynamic material basis and pharmacological mechanism of JBOL.
Drugs, Chinese Herbal/pharmacokinetics* ; Animals ; Tandem Mass Spectrometry ; Network Pharmacology ; Rats ; Chromatography, High Pressure Liquid ; Rats, Sprague-Dawley ; Male ; Idiopathic Pulmonary Fibrosis/metabolism* ; Humans ; Administration, Oral ; Protein Interaction Maps/drug effects* ; Signal Transduction/drug effects*

OBJECTIVES: To investigate the effects of early life intervention with Bifidobacterium bifidum BD-1 (B. bifidum BD-1) on hyperactivity in a female mouse model of attention deficit hyperactivity disorder (ADHD) and explore the underlying mechanisms. METHODS: Eight newborn female Wistar-Kyoto (WKY) rats and 6 spontaneous hypertensive rats (SHRs) were gavaged with saline and another 6 SHRs were gavaged with B. bifidum BD-1 (10⁹ CFU) daily for 3 weeks. Open field test of the rats was conducted at 7 weeks, and fecal samples were collected at weaning (3 weeks) and at 7 weeks for 16S rRNA sequencing. Immunofluorescent staining was used to detect dopamine transporter (DAT) and tyrosine hydroxylase (Th) levels in the striatum and activated microglia in the prefrontal cortex. Treg cells in the mesenteric lymph nodes, spleen and blood were analyzed using flow cytometry. RESULTS: The SHRs traveled a significantly greater distance in open fields test than WKY rats, and this behavior was significantly attenuated by B. bifidum BD-1 intervention. The expression of DAT and Th in the striatum was significantly lower in the SHRs than in WKY rats, while B. bifidum BD-1 treatment obviously increased Th levels in the SHRs. B. bifidum BD-1 intervention significantly deceased the number of activated microglia and increased Treg cell counts in the spleen of SHRs. The treatment also enhanced α diversity in gut microbiota of the SHRs and resulted in a decreased Firmicutes/Bacteroidota ratio, more active Muribaculaceae growth, and suppression of Clostridia_UCG-014 proliferation. CONCLUSIONS Early life intervention with B. bifidum BD-1 alleviates hyperactivity in female SHRs by modulating the gut microbiota and peripheral immune response, suppressing neuroinflammation and improving dopaminergic system function. These findings provide evidence for early prevention strategies and support the development and application of psychobiotics for ADHD.
Animals ; Female ; Rats ; Rats, Inbred WKY ; Rats, Inbred SHR ; Attention Deficit Disorder with Hyperactivity/therapy* ; Bifidobacterium bifidum ; Probiotics/therapeutic use* ; Dopamine Plasma Membrane Transport Proteins/metabolism* ; Tyrosine 3-Monooxygenase/metabolism* ; Gastrointestinal Microbiome ; Disease Models, Animal

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Methods: Thirty patients with PDVO of the lumbar or thoracic spine treated with transforaminal interbody debridement and fusion (TIDF) with AIBG between March 2014 and May 2022 were reviewed (AIBG group). For comparative analysis, 28 PDVO patients who underwent TIDF without AIBG between January 2009 and June 2011 were enrolled (non-AIBG group). The minimum follow-up duration was 2 years. Clinical characteristics and surgical indications were comparable in the two groups. C-reactive protein (CRP) levels and the postoperative antibiotics course were compared between the two groups. Results: Surgical treatment for PDVO resulted in clinical improvement and adequate infection control. Despite the shorter postoperative intravenous antibiotic duration (mean: 19.0 days vs. 39.8 days), the AIBG group had significantly lower CRP levels at postoperative 4 and 6 weeks. The mean Visual Analog Scale pain scores improved from 7.3 preoperatively to 2.2 at 6 weeks postoperatively. The average angle correction at the last follow-up was 7.9°. Conclusions TIDF with AIBG for PDVO can achieve local infection control with a faster reduction in CRP levels, leading to a shorter antibiotic duration.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Methods: Thirty patients with PDVO of the lumbar or thoracic spine treated with transforaminal interbody debridement and fusion (TIDF) with AIBG between March 2014 and May 2022 were reviewed (AIBG group). For comparative analysis, 28 PDVO patients who underwent TIDF without AIBG between January 2009 and June 2011 were enrolled (non-AIBG group). The minimum follow-up duration was 2 years. Clinical characteristics and surgical indications were comparable in the two groups. C-reactive protein (CRP) levels and the postoperative antibiotics course were compared between the two groups. Results: Surgical treatment for PDVO resulted in clinical improvement and adequate infection control. Despite the shorter postoperative intravenous antibiotic duration (mean: 19.0 days vs. 39.8 days), the AIBG group had significantly lower CRP levels at postoperative 4 and 6 weeks. The mean Visual Analog Scale pain scores improved from 7.3 preoperatively to 2.2 at 6 weeks postoperatively. The average angle correction at the last follow-up was 7.9°. Conclusions TIDF with AIBG for PDVO can achieve local infection control with a faster reduction in CRP levels, leading to a shorter antibiotic duration.